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development 2.0 series (renamed 0.6 series) of PyMVPA. If you are interested in the
documentation of the previous stable 0.4 series of PyMVPA, please
visit v04.pymvpa.org.
mvpa2.misc.transformersΒΆ
Simply functors that transform something.
Functions
| Absolute(x) | Returns the elementwise absolute of any argument. |
| Identity(x) | Return whatever it was called with. |
| first_axis_mean(x) | Mean computed along the first axis. |
| first_axis_sum_not_zero(x) | Sum computed over first axis of whether the values are not |
| grand_mean(x) | Just what the name suggests. |
| l1_normed(x[, norm, reverse]) | Norm the values so that L_1 norm (sum|x|) becomes norm |
| l2_normed(x[, norm, reverse]) | Norm the values so that regular vector norm becomes norm |
| max_of_abs(x) | Max of absolute values along the 2nd axis |
| one_minus(x) | Returns elementwise ‘1 - x’ of any argument. |
| rank_order(x[, reverse]) | Rank-order by value. |
| reverse_rank_order(x) | Convinience functor |
| second_axis_mean(x) | Mean across 2nd axis |
| sum_of_abs(x) | Sum of absolute values along the 2nd axis |
Classes
| ClassWithCollections([descr]) | Base class for objects which contain any known collection |
| ConditionalAttribute([enabled]) | Simple container intended to conditionally store the value |
| DistPValue([sd, distribution, fpp, nbins]) | Converts values into p-values under vague and non-scientific assumptions .. |
| OverAxis(transformer[, axis]) | Helper to apply transformer over specific axis |
